Career Growth Advice from Ria Cheruvu, AI Leader | Career Tips for Women in AI

2B Bolder Podcast – Episode 122
Featuring Ria Cheruvu, AI Architect at Intel

Episode Title: #122 Ria Cheruvu, AI Architect, ML Engineer and Data Scientist, Industry Speaker and Instructor

Host: Mary Killelea
Guest: Ria Cheruvu



Mary Killelea (Host): Hi there. My name is Mary Killa-Olea. Welcome to the To Be Bolder podcast, providing career insights for the next generation of women in business and tech. To Be Bolder was created out of my love for technology and marketing, my desire to bring together like-minded women, and my hope to be a great role model and source of inspiration for my two girls and other young women like you. Encouraging you guys to show up and to be bolder and to know that anything you guys dream of, it's totally possible. So sit back, relax, and enjoy the conversation.

Hi, thanks for tuning in. AI is one of the hottest technologies in the world today and a major driver of career growth and opportunity. Our guest today is a young woman with exceptional talent. Ria Cheruvu is an AI architect at Intel, machine learning engineer, data scientist, industry speaker, and an instructor. Rhea holds a master's degree in data science and a bachelor’s in computer science from Harvard University.

She's been featured in numerous publications on AI, holds multiple patents, and has spoken at prestigious events such as the Women in Data Science Conference, TEDx, and other top industry events. Ria is passionate about the importance of open source communities, women in STEM, and contributing in disruptive technology spaces.

Her area of expertise includes solutions for security and privacy and machine learning, fairness, explainable and responsible AI systems, uncertain AI, reinforcement learning, and computational models of intelligence. In addition to her technical work, Ria is a published poet, children's book author, and a neuroscience enthusiast.

Ria, thank you so much for being here. It is such an honor to have you on the show.

Ria Cheruvu (Guest): Thank you, Mary. I'm so excited to be here today and have a great conversation with you too.

Mary Killalea: Awesome. Okay. Well, you have achieved so much at a young age. And so here's some facts. I don't know if our listeners know, but I read that you graduated from high school at 11, became the youngest ALB graduate in Harvard history, and started working at Intel at 14. That is incredible. Can you share your journey and what it was like to land your job at 14 at Intel?

Ria Cheruvu: Oh, thank you so much. And definitely, I think it was a fantastic journey that was filled with lots of great moments and helping hands too. So, I graduated high school when I was 11, as just mentioned, and, you know, it was basically a lot of the kind of planning I'd say in the forethought that my mom put forward as part of my curriculum. She was my learning coach and there with me every step of the way. And, you know, basically helped me design a journey that was accelerated, that was meaningful. And that was also really kind of exciting to kind of pursue challenges. And then, you know, after that, I enrolled as part of, you know, the computer science programs at the university and basically, you know, started there.

And after I had graduated with my undergraduate degree in computer science, I joined Intel as an intern. And at that time, one of my mentors helped onboard me into the process. So I basically interviewed the three different teams that were all related to AI. And I had the opportunity to, you know, if gotten a go from all three teams, which I'm grateful I did to basically select the team that I was interested in. And I went ahead and selected a team on deep learning and architecture. And then again, I'm so grateful to my mentor. He's the one who kind of completed all the onboarding forms and the documents and things like that to help me get my first internship at 14 at Intel, which was super exciting.

Right before that, I actually had an academic internship at Yale at the clinical neuroscience imaging center. So I had some experience with, you know, what it means to kind of be in that environment, to, you know, start having deliverables and pursuing them in the CS space. But working at Intel has definitely changed my career and my life for the best way. So that's a little bit about me and my journey.

Mary Killalea: That's incredible. And I don't know what the other options were, but for you to have had the foresight to know that AI was going to explode and be so relevant and what a great career path you chose early on is amazing.

Ria Cheruvu: Thank you. And again, I think full credit goes to my parents and also mentors for that one, Mary, because both of my parents are computer scientists by trade and have worked in a lot of different really interesting roles. My mother was really on the data analysis side and now she has, you know, her degree in philosophy and does a lot of work on that side. And then my dad is kind of more on the security side, so very specialized and then embedded and, you know, firmware, et cetera.

One of the things that my mom and I were very interested in while I was growing up and something she invited me is kind of an interest in neuroscience, which is a really fascinating still to this day. And that naturally kind of led to an interest in AI, right? It's the perfect blend of disciplines between understanding neuroscience and then using AI as a way to kind of mimic neuroscience. So that's kind of how it started. And then it just kept bubbling over. Now, at this point in time, I've been at Intel for, you know, six years. I've been working in AI for about eight years, counting the time that I was working on projects during my degree and as part of my internship at Yale. I'm returning to a point in my career where I'm excited to get back potentially into neuroscience and psychology. So I think it's a really nice kind of roundup of, you know, using AI and tying it together with cognitive computing and neuroscience. And I really have to thank my parents, my mom especially, and also my mentors who were, you know, right at the get-go were saying for you, you know, AI is a booming field. This is the perfect place to kind of transform and explore challenges and solve.

Mary Killalea: That's so fascinating. How have you navigated the challenges of being the youngest person in many business settings or academic settings as well?

Ria Cheruvu: Yeah, I mean, I think there's, I'm personally blessed to know, have seen a lot of significant challenges or challenges at all when it comes to discrimination and things like that. I've never kind of experienced that at Intel, which I'm very grateful for, and also at Harvard too. So I think it was a pretty seamless experience. Everyone was always very welcoming, make space to kind of explore ideas. And, you know, basically, again, it's when I say challenge, you know, pushing back and forth on assumptions and being able to kind of push the envelope, right? And keep innovating on better things and, you know, creating better solutions. So I definitely say that I'm very grateful for that kind of pocket or envelope of having the opportunity to explore those things.

Of course, there's general workplace hiccups that happen at any point in time. And I think, again, you know, I'm kind of back to relying on my community and the folks that I can always reach out to and ask for advice and help and, you know, connect with to understand, hey, what is the next best step for me to take in my career, right? Or what can I do to overcome this particular hiccup or hurdle or maybe, you know, lack of interest, right? Or maybe a need to get challenged further, right? So I think that it's a community has been a really big aspect for me, personally, to get past that.

Mary Killalea: That's such a good thing to call out for, you know, the younger people entering the workforce, you know, many wait to build their community, but having it at the get go adds so much clarity or guidance, I guess you could say.

AI covers so many areas. Tell us about your primary areas of focus and interest within AI. I know I mentioned a few in the intro, but why you chose those and what leads the passion there?

Ria Cheruvu: Yeah, so I think there's a couple of disciplines in AI that really speak to me personally. So I think it's changed over the years.

When I first kind of started off my career path, Mary, I think it was really focused on, again, that connection to neuroscience, right? So a lot of it was on, you know, statistical data analysis, like of FMRI images. And then the other part of it is something that I still kind of smile about when I think back about something called neuro cryptography, which was a really interesting blend of using neural networks and security algorithms. And I hope that the field gets revived. It was a very niche field that, you know, it's still only a little attention is given to it. But I'm sure as AI models, popularity and complexity increases, we'll get back to using neural networks for, you know, encryption protocols and other elements. And quantum computing is definitely going to accelerate that, right? But that's kind of where it started.

In the middle of my journey, at Intel I got introduced the idea of the end to end stack, right? How do AI models and in general, the things that we interface with work from the chip level all the way to the front end web interface level, like how voice assistants are working in smartphones or how our laptop can blur our background, right? And all of these really fun, interesting facets of the technology. And then I'd say after that, it's just a progression, but there's also kind of interesting technologies around, you know, cognitive computing and reinforcement learning, the idea that AI models can scale up and learn and, get feedback from their environment.

And that's led me to my current interests today around human centered AI and AI that is capable of learning and adapting to different environments, right? So I'd say that's kind of been my progression of interests and areas of AI. And that allowed, allows a lot of AI developers and programmers to touch all of these different areas from, you know, basic foundational neural networks and machine learning models and data analysis all the way to these, you know, complex paradigms.

Mary Killalea: So fascinating. As an influencer and an advocate for AI, what do you hope to teach others most about this field? Because, you know, there's so many things worrying people about AI today. What is it that you hope to, I guess, have an impact on the people that follow you?

Ria Cheruvu: Yeah, I mean, I think there's two facets to that. The first one is that it's easy to get started. And it is a great kind of opportunity and a field to get into, even though the hype may, you know, die down. I know now, all of a sudden, at least across LinkedIn and other social media networks, the new boom is starting to become quantum computing with Google's announcement, right? So a little bit of the focus has shifted from AI to quantum and some hybrid things there. But regardless of where the hype goes, I think that there's a lot of value in the AI technology space for just building really cool applications that are smart and intelligent and reactive. So there's an increasing need for young talent that is just willing to break assumptions about the technology and start to say, hey, what can I do with this? Right.

And then I think the second aspect of that, that I want to be more vocal about, and I think be able to represent better as I grow in my career is that community aspect as well. That we discussed earlier, right? I think it's just that general idea of what it takes to be a leader in tech and what are some of the decisions you have to make, because you're going to get a lot of criticism from folks that you don't know, right? For making decisions that you may know are right or that your community and your mentors have told you are right. And sometimes you just have to go with the flow, right? Everyone's career journey is different and the impact that you deliver is definitely going to be different than what a colleague is going to deliver because it's customized or ideally it's customized to your interests and to your passion and problem statement. Right. So I think that those are the two things that I'm continuously learning about.

And I, you know, I always, almost every other day I ask my mom for advice on these, because it's just so important as a young person in tech to figure out what's my next step? What do I do that can make a difference? So I would encourage folks on my generation and of all generations, right? I think it's a really interesting, you know, set of questions to ask ourselves as we continue to grow in AI.

Mary Killalea: Well, I think the fact that you're asking yourself, what difference can I make is by far the biggest thing that anyone can do. What advice do you have for women who are trying to find their voice and build confidence in their careers?

Ria Cheruvu: I'd say the number one thing to recognize is what it takes to be an expert, I think is not typically what we think it is. I've had a lot of conversations with women and colleagues in the space who wanted to learn, for example, data science and data analysis, which is a topic, a specialization I got my masters in. So, you know, when you get a degree, it's generally known that, hey, you know, you're an expert in this space. But I think that things are changing now, right? Regardless of certifications and degrees, right? Internally, to build a confidence to be able to speak about something, you need to recognize when you're comfortable with calling yourself as an expert. And it's not going to come at the standards that society may put out, right?

Because again, you know, to be an expert, let's say in computer science, maybe you need to know a bunch of programming languages and be able to be a super efficient coder, right? You can manage all these tasks, right? But maybe that's not what an expert means in, again, your interest area, your problem field, or what it means to you, right? So I think identifying the boundary at which you believe that you have the expertise you need to communicate and to strongly represent yourself is really critical. It doesn't mean setting the bar lower for ourselves or too high so that we can never achieve it, right? But it's that balance.

Mary Killalea: Yeah, no, I completely agree. And I think, you know, one thing that I've heard from many women is just, you know, not having that fear to raise your hand in a meeting and to speak up, even though, you know, you may not be that so-called expert, your view and why you're in that room matters. So, to not be quiet and sit in the corner is, you know, one action that each woman could take.

Ria Cheruvu: Exactly. I completely agree with that. And I'd say that that action and the idea of implementing it makes you an expert in certain domains, right? Because it means that not only do you understand a subject or a topic enough to be able to voice something about it or ask a question, but you're actually taking action and doing something about it. And I've noticed that, you know, especially in the corporate world, and I would love to get your thoughts on this too, that's kind of what it takes to be a leader from my understanding, which is actually doing something about, you know, a topic or an area, asking questions and, you know, that's how you start making a difference.
Mary Killalea: Absolutely. No, I found my time in corporate that, one, when you work remote, be on camera so that people can see you and see that you're engaged and be engaged, but then also to ask those questions. And maybe, you know, you might know that answer partially, but for the people in the room that are less willing to ask those questions, I also took on that kind of advocacy role in my time.

Ria Cheruvu: Absolutely.

Mary Killalea: Who have been, and I think you touched on this earlier, but beyond your parents, who have been most influential in your life?

Ria Cheruvu: Yeah, I mean, I can definitely reference so many different mentors and teachers and professors over the years. Steve Tu, is the primary mentor who onboarded me to Intel and helped me with my internship process. And at Intel, I've had the pleasure of being mentored by and having communications and networking with so many brilliant leading women in the space. Lamma Nachman, who leads Intel's responsible AI efforts, is one of the amazing women who's kind of a trailblazer in these efforts.

Also, Humma Abidi, who has now left Intel, but, you know, she and her team are always kind of, have been a shining star during their time at Intel and also continue to be a long lasting legacy of brilliance and technological innovation that I always look up to.

And so many other fantastic colleagues, Dr. Hal Blumenfeld from Yale University, who kind of first helped me learn about the details of an internship, as I mentioned earlier, it still plays a really key role in kind of inspiring me to kind of keep shooting for interesting new ideas.

And although, you know, sometimes you're not that much in touch with certain folks just because of time, right? I think they're always kind of part of your network or you're always able to reach out to them, which I'm so incredibly grateful for. So I definitely say these are some of the few folks that are kind of very, very close.

There's also a lot of fantastic, you know, VPs at Intel as well that I've had the pleasure of networking with as part of conferences, right, like Pallavi Mahajan, and others, and they're really fantastic women who are just always there, and ready to reach out and of course, brilliant leaders.

Mary Killalea: That's fantastic. And I love that you've had external influencers and mentors along the way. And I certainly don't want to discount your parents because it starts with parenting, you know, the positive influence. What do you think they did right to nurture the love of learning in you?

Ria Cheruvu: I mean, I've reflected on it a lot as I've been growing up. I think one of the fundamental things is, you know, my parents themselves have a love for learning. So it was kind of like a monkey see monkey do, which is what I like to call it. But it's just the general idea. And I mean, again, I think that there's a lot of areas where I find myself stumbling to, where I kind of look up to my mom and dad and see how they react to things, right, and how they get excited about, you know, learning new topics, new areas, and getting past those problems or those roadblocks and always being excited to kind of explore the new things. I mean, my mom and I talk about this sometimes. And, when she was reading books to me when I was little, like her excitement around, flipping the pages and looking at the new things, that's kind of what I think got imprinted onto me.

So anytime I'm not feeling excited about something, I go and run it by her, honestly. So, am I, having a little bit more of a lower vibe right towards it? Does that kind of match where I want to be? Right? Because, you know, there's not, there's always kind of an opportunity for us to maybe take a step back when there's an opportunity, instead of taking a step forward, because you're not really sure if that's right for us or not.

So I think having her as a mentor or guide that you can rely on and say, hey, is this exciting? Like, do you see the value in this? Or, you know, do you see value in, you know, another area? I think that that's been absolutely crucial for me personally.

Mary Killalea: AI has such a broad potential. How do you see it impacting career opportunities specifically? And what roles do you foresee being created or eliminated in the short or long term?

Ria Cheruvu: It's a great question. I think AI and the job market has so many interesting conversations and corollaries. On one end, there's the talent for CS students and in general, any area that's intersecting, you know, applications, right? And computers, right? I know friends in aviation and in healthcare, etc. and all of their fields are kind of getting impacted by AI, either directly or indirectly as part of, maybe professors telling them to integrate it as part of their projects or being incorporated in courses, right?

So I think skilling up for the AI revolution is an incredible idea. And also very accessible with a lot of the resources sitting on the internet, a lot of the free courses and material. And then if you have the budget to pay, right, the certifications, the degrees, the pathways, depending on the credentials and the jobs and the roles that you're reaching for, there's an immense opportunity on that front.

On the other front, there's the general idea of disruption, right, with AI and the job market. And I know it's a very hotly debated topic. So to put it kind of very lightly, I'm personally an advocate for, you know, human centered AI related developments and algorithms and models, right? This idea that, you know, on one end, we're encouraging AI models and the innovation there, but we're also being very careful about what exactly is the role of a human in being able to kind of participate, right, in the algorithm development or in the feedback of the algorithm, right? And, you know, creating an environment basically where both parties are kind of being able to interchange and then provide inputs and outputs. Again, it's, I think, an incredibly nuanced topic from everything from like autonomous vehicles where maybe you want your vehicle to do fully self-driving so you can focus on phone call or managing family members in the back of the car, right? And again, it depends on the perspective, right? Or if it's, you know, again, a hybrid, right, where you don't want an AI model that's automatically screening your resume to miss it just because you missed a couple of keywords, right? So I think, you know, a lot of key nuances, and I think that's where the human centered AI technology definition really comes into play.

Mary Killalea: Are there AI tools that you would recommend people, like more non-technical people use? Like, I know there's ChatGPT, but do you recommend people start using those tools today to accelerate their brand, you know, getting, like, I think that's one thing that I try to teach people because I use it within my own business. And so what are your thoughts on using ChatGPT to work on your personal brand and what other tools would you recommend?

Ria Cheruvu: I mean, I definitely agree with it. And my response may have been a little bit different personally a couple months ago compared to now, but I've personally started to use tools like ChatGBT, Claude, Gemini. I'm still just starting to use Gemini as a little bit different, but Copilot and others for personal brand development. The best thing I think about AI tools that are kind of writing oriented or text generation, if you want to use the right word, is that they can kind of communicate about your personal brand in a way that's very objective and fact based, that we may not be able to convey on paper.

So again, I'll take an example of my mom because I love her and we always have these really great conversations. I apologize if I keep reusing them, but she just started a small business where we live in Arizona. And one of the key things is to write your bio. You want it to be catchy, something small. And ChatGPT did a fantastic job of taking a list of accomplishments and summarizing it into something that's impactful, something she's complimented about. But it's kind of challenging to write on your own, especially when you don't know maybe how to articulate your work because it happens, I think, to all of us. So I definitely recommend the use of these tools for branding.

Of course, there's other ones like text to speech. If you want to just kind of say some things out loud and you want a model to kind of transcribe and take care of it for you. Even diagramming tools, AI diagramming tools, can be really helpful in just trying to put your vision on paper or on a PowerPoint or something like that to kind of get started with defining what you want to do. So I definitely recommend it.

Mary Killalea: It's amazing that all the different tools out there. I mean, really, if you think it, it's probably out there in some type of app already. So, it's just knowing what to look for and going to those tools and educating yourself. You probably look it up on YouTube and get a lesson.

Ria Cheruvu: I'd say the one tip that I've learned regarding finding the right tools, though, because again, there's a lot of hype out there, a lot of tools that kind of get shoved in our face sometimes is whatever is kind of generally more popular, I'd say within the community is definitely something to go for first.

For example, I think that these text generation tools like Claude and ChatGPT are very popular and that's where we kind of see the most value. There are these smaller applications, just as you mentioned, Mary, right? Again, like I mentioned, text to speech transcription or diagramming, but there's so many different applications that have popped up there. So I always go first towards the ones that are more popular. And once I've kind of examined them and understood the way that they work further, then I kind of dive into ones that are a little bit less used, less popular, maybe don't have that good of a videos or documentation or guidance around them, because you kind of ease yourself into the entry of what the tool looks like and what to expect. So you're not settling for less, right? You get the expectations and the quality of the tool that you want to work with. So that would be my recommendation for non-technical folks getting started with AI tools.

Mary Killalea: That's awesome, because I think there's so many people out there that are looking and needing and wanting to pivot in their career. So, knowing where they can start to embrace the technology, because during interviews, if they can speak to the fact that they are using AI or are adaptable or have that growth mindset around AI, I think that's a selling point, because most companies are integrating AI in one way or another these days. But for those who are already technical, because many women in tech listen to this, what do you have advice wise for maybe careers that they can go into that kind of accelerate their growth?

Ria Cheruvu: Okay. I think it depends kind of the way that I've started on it. And I have encouraged my friends and colleagues to look at it. If you're interested in AI and data science in general, is to kind of think about the end to end stack of a problem statement you're interested in. That's how it started for me. I was interested in autonomous vehicles as an example, and then the other neuroscience side of things.

But taking autonomous vehicles as an example, there is everything from the sensor data fusion that's installed on the cars like LIDAR sensors, all the way down to the chip level embedded computing and algorithms that you run there. And then the AI models and the interface that are doing object detection, pedestrian intent estimation. I think that anchoring on the specific algorithms that seem interesting and the questions that we get, like how is this AI model in this car able to detect that somebody is walking next to it, or how was it able to create a 3D model? Each of those questions opens up an entirely new career path, I would say. Or not even a path, but an interesting specialization and a set of skills and tools and knowledge you can gain.

For example, on the object detection path, which is very popular in the AI space, it opens up this idea of using different toolkits like yellow algorithms from ultralytics and other types of libraries and capabilities around founding box detection and optimization and false positives and failure analysis.

You can create projects and tailor a resume and then start to apply for jobs, let's say, in the computer vision engineer or deep learning engineer or AI engineer space. Whereas if you're interested in the chatbot space, you're looking at large language model, foundational model definition, AI agents, lane chain, Lana index, a lot of those toolkits. And you target your focus there, learn the skills, add it to your resume, and then keep moving forward. That would be my recommendation from what I'm learning to keep up to date with the rapidly changing pace of the tools and to get those skills on our resume and start looking for jobs that really interest us.

Mary Killalea: That's fantastic, because not only did you talk about the path in which someone could go about doing that, but you brought up a really good point, and that is, I think, being drawn to what you're interested in and then reverse engineering. How do I get into that space and educate myself? And then what did I do to learn that and then communicating that in your resume?

Ria Cheruvu: I would definitely say that that's the approach to go. And in some cases, you learn that kind of the painful way where you get involved in a project that you think is going to look really good on your resume. A couple of days in, you realize there's not a lot of good documentation. There's not a lot of maybe good communication just because teams are working on different things. It's hard to intercept. But at the end of the day, outside of all of the excuses, and I've done this personally, you kind of realize that you're not interested in it really that much. And the interest that you felt going in was about the potential, but not about the implementation. And it can be kind of like a rock that you keep pushing through and you're saying, OK, I do need to do this. But at the end of the day, if there's something more exciting that's catching your attention and you feel like that's something you could easily do, maybe it's worth it to take a pause, if you can, from this project that's kind of not really your interest point and go and solve some challenges and tackle the frustrations of what you're interested in, what you're drawn to.

Because I think as engineers at a certain point, we get excited about everything in terms of the potential to do and then make a difference. But that potential can wear down when you hit the implementation roadblocks. So I think it's important to kind of think about and choose a area or look for the opportunities that come to us, about things that interest us that allow us to kind of keep overcoming those hurdles.

Mary Killalea: Shifting gears a bit, speaking of things that you love and that you're drawn to. I think it's fascinating that you wrote a book, Forest Mystic. Tell me what was the inspiration behind that. I just love that you wrote a children's book.

Ria Cheruvu: Thank you. I appreciate it. And thank you for breaking it up too. I've always kind of loved poetry since I was a kid. I've stopped it recently, but I'm hoping to get back into it. And the really cute stories, again, I have to credit my mom for the idea of the story for this one, because it was basically a small, tiny story that we came up with and then we modified the moral of the story.

It was actually based on stories as a kid that I got into and that I heard and then we decided to take some pictures from vacations and trips that we've taken, turn it into a nice cute little poetry book that our friends, kids loved it. I think neighbors loved it too. I think it's just kind of a small way of exploring an interesting story. And I think, interestingly, the moral of the story that I recognize now that I'm older for that book is that it's important to kind of… It's actually about community, right? It's important to ask for help when you need it and also to kind of learn from recognizing when help is being given to you and what is genuine and what isn't, right?

So, the hero of the story, or one of the protagonists is a prankster who kind of learns that throughout the story. And it's just like a very interesting idea of why community is important, why being genuine and kind and friendly is so important to kind of grow.

Mary Killalea: I just enjoy talking to you so much. What non-technical skills or attributes have you found most valuable in your career?

Ria Cheruvu: I know that there's the major ones that are mentioned, which is communication, which absolutely is so, so critical that I still work on, right? Confidence is another thing that I'm currently working on, which I think it's just around representation and I've seen and I learned a lot from our prior conversations too from you on this. And, you know, I think just reiterating that it's so, so crucial from my understanding to kind of have that presence and that confidence while you're speaking.

I think another key soft skill that I've learned is rest, which is in and of itself a soft skill, right? When you're about to give a big speech of really detailed technical demo, starting on a coding project or starting to map out, you know, your career path or even communicate with, you know, you know, stakeholders or anything like that or start a new side hobby or project, having that opportunity to take a moment to rest, to kind of introspect briefly before going forward is so critical. It's kind of like that self-talk aspect. So that's the third main soft skill I would emphasize on.

Mary Killalea: That is great because I don't think many people bring that up and that is so important for clarity of just the mind. Okay, with so much noise around AI, what are some good resources, books or podcasts or influencers that you would recommend people tune into or read for future learning?

Ria Cheruvu: Yes, I think I also mentioned this in a recent interview with Mashable about these two brilliant, brilliant women leaders and pathfinders in this space that I would, I again follow them. So, I encourage usually whenever I talk to my network for folks to follow them too.

Fei-Fei Li, who has kind of pioneered ImageNet and a lot of the really great AI technical innovations. And then Yejin Choi, again, I apologize. I don't know if I mispronounced her name, but she is also an incredible kind of leader and a pathfinder in really interesting areas. I think I first kind of got familiarized with her research in the context of moral databases and mapping for AI models, which was really interesting in the context of what's happening in the AI space going forward.

So I definitely recommend those two amazing folks and then there's also Sebastian Braschka, who does an amazing set of technical resources. I'm still trying to find time to be able to go through them all, right? So that's kind of another fantastic, brilliant kind of engineer in mind to follow.

There is also another set of resources. I'm forgetting the name of the professor who pioneered them, but it's called AI by Hand. And I follow the professor and the researcher who does those implementations on LinkedIn. Really a fantastic deep dive down into the technical mechanisms of AI, which are, he makes them super fascinating, super digestible to understand. And it's always kind of a joy to even browse through it if you don't have enough time. So definitely those are the best resources to kind of follow. Again, they're kind of super technical. If you're looking for more high level ones, I definitely think that some of these organizations that are doing some good AI research that we are interested in, like maybe Microsoft or Google or OpenAI, right? Their blogs are really interesting ways to kind of keep subscribed to the latest and greatest, right? Again, depending on whether you like their implementations, you're interested in their toolkits and technologies, that's another really great resource, the technical blogs there.

Mary Killalea: Do you teach as well?

Ria Cheruvu: Yes, I do teach. I'm super passionate about teaching. I'm actually in the middle of creating a course right now on interview prep for data science and machine learning, but I've taught eight courses so far in the past two years. It's been quite a journey, but I absolutely love instruction.

Mary Killalea: Okay, well, of all those people that you listed, I want to make sure that you and I connect afterwards and I get that list and I'll include it in the show notes. And then when you publish your newest lesson, I want to make sure I include that because that sounds fascinating.

Ria Cheruvu: Thank you, Mary. Absolutely.

Mary Killalea: So how do you unplug from work and I guess reboot or recharge yourself?

RC: Yeah, I mean, I love to hike, especially it's kind of beautiful this time of year in Arizona. So I'm motivating myself to do more hiking, right? And to get more exercise. I also love swimming. It's my favorite sport out of everything and especially it's just so wonderful to kind of cool down and to relax. That also gives you a great workout.

In addition, reading is really fantastic. I think now my kind of latest interest has been finding these older books and novels that are kind of, 1960, 1970s, right? And then just reading them through if you can find them in your library, right? Because, you know, it's so interesting to kind of see how the same concepts that are discussed in those books can still apply today. I think it's just so fascinating without, you know, zero changes, honestly, in terms of the transfer of the concepts. So it's really fascinating. And books on psychology and other really cool stuff. And games, of course, love to play games with friends and digital, physical, it doesn't really matter.

Mary Killalea: That's awesome. Okay, so what does to be bolder mean to you?

Ria Cheruvu: To be bolder means being able to understand and create a value definition for yourself. And I know that sounds a little bit corporate, but the general idea that you kind of have value inherently. And whatever you do, you kind of bring that to the statement, whether you're tired, or you're not energetic, or you're at your best, and you're thriving, you inherently have value, regardless of everything that's happening in your life. And seeing how that kind of grows, as you experience different experiences and circumstances, and, you know, whether it takes a setback or a step forward, kind of seeing how that value grows and nurturing it, I think that's what it means to be bolder, which is really seeing that value in ourselves inherently.

Mary Killalea: I love that unique perspective. Where do you see yourself in five years, say, or 10 years?

Ria Cheruvu: That's a great question. Probably a CEO of a multinational corporation is the goal. And I'm counting on my network and my community to keep me accountable to it. And, you know, I've got a lot to learn to get to that point. I think a lot on leadership and, you know, again, confidence, right, and stepping into spaces. But I'm always open to mentorship and to advice and to opportunity. So, yeah, I'm going to shoot for the moon and see where it takes me.

Mary Killalea: Well, I'll buy stock in that company for sure when you're leading it.

Ria Cheruvu: Thank you.

Mary Killalea: That's amazing. Okay, before I let you go, just some quick rapid fire fun questions so people can get to know you. And I know this this interview has been not focused on all the wonderful things and deep dives that we could take in AI. But I wanted to make sure that I had you on our show just to talk about careers, because I think that's such a good opportunity. And you really are inspiring to so many women in STEM. And I just I think if you don't hear it enough, thank you for that.

Mary Killalea: Okay, so pizza or pasta?

Ria Cheruvu: Pasta.

Mary Killalea: Dogs or cats?

Ria Cheruvu: Cats.

Mary Killalea: Summer or winter?

Ria Cheruvu: Winter.

Mary Killalea: Ice cream or cake?

Ria Cheruvu: Cake.

Mary Killalea: Comedy or drama?

Ria Cheruvu: Comedy.

Mary Killalea: All right, I'll let you go. But before I do, thank you so much for being here and sharing your story with us.

Ria Cheruvu: Absolutely. Thank you so much for having me, Mary.

Mary Killalea: Thanks for listening to the episode today. It was really fun chatting with my guests. If you liked our show, please like it and share it with your friends. If you want to learn what we're up to, please go check out our website at 2bbolder.com. That's the number two, little b, bolder.com.